Results 111 to 120 of about 195 (132)
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Matrix free computation of C.R. Rao's MINQUE for unbalanced nested classification models
Computational Statistics & Data Analysis, 1984The paper presents a calculation of Rao's minimum norm quadratic unbiased estimators (MINQUE) for variance components and a generalization of the matrix-free technique of Hemmerle to an arbitrary weighting matrix in the case of nested classification models.
Kleffe, J., Seifert, B.
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Zur anwendung der schätzmethode minque auf probleme der prozeβbilanzierung
Mathematische Operationsforschung und Statistik, 1973The recently developped theory of MINQUE and r-MINQUE estimators is applied to a special class of probleii-1s arising for example in the chamical industry if a certain mea-suring arrangement is recovered repeatedly by values. From the mathematical point of view, the question concerns compensation problems where, however, the weights are unkniiwn in ...
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Assessment of observations using minimum norm quadratic unbiased estimation (minque)
CISM journal, 1990Estimation of the variances and covariances of observations in geodetic and engineering surveys of high precision is of great importance for proper weighting of the observations in their subsequent processing and for better understanding of sources of errors and their modeling. The authors have adopted from modern statistics the Minimum Norm Quadratic
Y.Q. Chen* +2 more
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On the role of minque in testing of hypotheses under hiked linear models
Communications in Statistics - Theory and Methods, 1988Testing of hypotheses under balanced ANOVA models is fairly simple and generally based on the usual ANOVA sums of squares. Difficulties may arise in special cases when these sums of squares do not form a complete sufficient statistic. There is a huge literature on this subject which was recently surveyed in Seifert's contribution to the book of Mumak ...
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Über die schätzmethode minque von C. R. Rao und ihre verallgemeinerung
Mathematische Operationsforschung und Statistik, 1972The authors give a very simplified proof of the construction procedure of the estimation principle MINQUE presented by C.R.RAO. They show that every MINQUE estimation can be constructed in this manner. They further generalize this procedure to the r-MINQUE principle involving a larger class of problems.
Focke, J., Dewess, G.
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C. R. Rao’s MINQUE for Replicated and Multivariate Observations
1980Assuming a basic variance-covariance components model we derive C. R. Rao’s MINQUE for its m-fold replicated and its multivariate version. Both extensions do not essentially increase the extent of necessary calculations and our formula for replicated observations gives some new light on the asymptotic behaviour of MINQUE.
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จากการที่ปัจจุบัน การรังวัดพิกัดด้วยระบบดาวเทียมจีพีเอสได้กลายเป็นเครื่องมือสำคัญสำหรับงานที่ต้องการความละเอียดถูกต้องทางตำแหน่งสูง ในการคำนวณเพื่อให้ได้ค่าพิกัดที่มีความถูกต้องสูงจำเป็นต้องมีการกำหนดแบบจำลองทางคณิตศาสตร์และแบบจำลองสโตคาสติกให้ถูกต้องและใกล้เคียงความเป็นจริงให้มากที่สุด เทคนิคการคำนวณหาค่าต่างเป็นแบบจำลองทางคณิตศาสตร์ที่นิยมใช้ เน ...
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Eine Bemerkung zur Anwendung der MINQUE-Methode
1977In dem von Hildreth und Houck (1968) vorgestellten linearen Regressionsmodell mit stochastisehen Koeffizienten lautet die t-te Gleichung $${{\text{y}}_{\text{t}}} = \mathop \sum \limits_{{\text{k = 1}}}^{\text{K}} {\text{ }}{\beta _{{\text{tk}}}}{{\text{x}}_{{\text{tk}}}} = \mathop \sum \limits_{{\text{k = 1}}}^{\text{K}} {\text{ }}\left( {{\beta _{
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C. R. Rao's minque under four two‐way anova models
Biometrical Journal, 1980AbstractThis paper presents C. R. RAO'S MINQUE along with their sample variances under four normal two‐way ANOVA models. The resulting formulae are similar to the ANOVA sums of squares, equally easy to handle with and may also serve to calculate restricted maximum likelihood estimates in a highly efficient way.
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Journal of the American Statistical Association, 1972
Abstract Let y = Xβ+e be a Gauss-Markoff linear model such that E(e) = 0 and D(e), the dispersion matrix of the error vector, is a diagonal matrix whose ith diagonal element is σ2 i, the variance of the ith observation yi. Rao has recently brought out two sets of sufficient conditions (on X) for the MINQU-estimability of all the heteroskedastic ...
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Abstract Let y = Xβ+e be a Gauss-Markoff linear model such that E(e) = 0 and D(e), the dispersion matrix of the error vector, is a diagonal matrix whose ith diagonal element is σ2 i, the variance of the ith observation yi. Rao has recently brought out two sets of sufficient conditions (on X) for the MINQU-estimability of all the heteroskedastic ...
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